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    <br/>第二章 Java 数据分析算法引擎系统
    <br/> 作者: 罗瑶光, Author:Yaoguang.Luo<br/>
    <br/>
    <br/>基础应用: 元基催化与肽计算 编译机的仿生分析机
    <br/>

    <br/>计算力与算能优化的思想手稿 20190914
    <br/>
    <br/>最近有WCC1st 长沙 拜听了中科院超算 老师们关于计算力的趋势发展做的详细发言, 深有感触,
    于是结合自己 10 年基础所学和 6 年国内外工作和实习的经验, 写一篇我关于计算力的细节, 应用和
	发展趋势的理解手稿.
    如下.
    <br/>
    <br/>计算力的概念 我所理解为 计算能. 这是未来世界发展的一种能源, 算能. 算能 不是新能源,
    但是, 算能的认知, 的确是新的篇章. 算能的利用率逐渐接近人认知的最大化. 更为高效的 算能 挖掘方式,
    是目前主流科学家们一直保持白热化研究的主题. 10 年前, 社会很少出现这类词汇, 我得到一个明确的细节,
	社会的白热化发展趋势, 必然 新型算能, 能源在被挖掘中.
    <br/>
    <br/>比如:
    <br/>
    <br/>1 基础算子能: 就是通过非人类所能理解的算子列阵来代替线性的公式来做复杂运算. 比如DNA
    计算, 德塔的 DNA mask 列阵 Initon 链 就是一种. 2 量子算能: 通过量化的概率比来对带有计算
	物质进行处理, 比如波动微观物质的波动概率, 向量集的比例计算, 神经网络的 算核卷积等. 3 光算:
	通过不同频率的电磁波进行耦合计算, 达到极度并行算法 散列算力加速. 4 微电的超导计算: 在完全
	没有阻力的电信号运算, 永不失真. 我评估了下未来的算能发展趋势为: 从经典到非认知, 从可控到主猜测,
    从自主到自适应, 从无机到有机体的过程需求离不开市场, 这些 新型算能怎么转化为人类科技呢?
    我想到了一个答案: 机器人.
    <br/>
    <br/>上面的部份 强调新型算能改变算力的趋势.
    <br/>
    <br/>这个部份我思考了更多细节来优化新型算能过程.
    <br/>
    <br/>1: 计算逻辑的理解方式. 通常我们认为所能理解的计算逻辑是按照 类人认知的思想, 把社会需求
	封装成计算函数的过程. 这个过程终究是人所能理解的范畴. 机器是人做的, 具备人的思维共性可是机器
	在计算质量上, 以后终将超过人类, 那么问题就来了, 不被理解的逻辑和思想所形成的概率比, 以后只会
	越来越大. 很多不被理解将成为趋势, 法律约束问题, 我们暂不讨论. 接受和顺应一些新的思维方式, 必然
	不断冲击着人类社会的科技和伦理. 这是一个社会变革所能产生的巨大压力来源. 解决和研发方案以后要有.
    <br/>
    <br/>2: 计算数据的采集模式. 计算的数据形形色色, 不同的模式下, 数据表现得形式也不一样, 能够
	通过某种观测模式, 把数据进行迅速有效得预处理, 是一个重要主题.
    <br/>
    <br/>3: 计算过程的相似度过滤机制. 计算得数据多种多样, 计算逻辑千姿百态, 可是计算过程却极其相似.
    而相似度高的组件重用, 逻辑优化, 信息归元, 是算能优化的科学方向.
    <br/>
    <br/>4: 计算结果的验证优化. 计算结果是需要检测维护的, 检测时手段直接确定结果的区间有效性.
    我们需要更多的思考.
    <br/>
    <br/>5: 计算进化的知识图谱统计. 计算, 实现终究是硬件, 软件的有机体组成, 这个组成系统终究是
	变化的. 正确的进化和升级直接改进算能体系. 统计学能准确的进行测量计算进化过程中的各种数据数值
	多观测点分析. 当然, 还有很多想法, 我不敢多写, 因为没有得到实际的论证, 将来有机会涉及它的细节,
	我会反复的实践来明确答案.
    <br/>
    <br/>最后: 如果我能进行定义, 我定义 计算算能优化公式为 真实环境中 每 1 秒 函数执行需要走的
	硬件逻辑门(与或非总数 S)与 软件函数本身执行需要的(与或非总数 s)的比
    <br/>
    <br/>公式为 N =S(AON)/s(AON)
    <br/>
    <br/>N= 算能单位
    <br/>
    <br/>AON= AND +OR+ NEGATIVE (与或非门器件)
    <br/>
    <br/>S= 每时间秒函数在非结束状态走过的 AON 累计总和 (微秒 对应 微 N, 纳秒 对应 纳 N)
    <br/>
    <br/>s= 函数本身执行需要走的非重复 AON 单元总和
    <br/>
    <br/>20190914 北京时间 4:34 罗瑶光
    <br/>
    <br/>注: 通过这个函数可以确定函数优化前后的计算能力值, 确定优化是否有效.
    <br/>
    <br/>罗瑶光 20190914
    <br/>
    <br/>Computing and Its Energetic Optimization
    <br/>
    <br/>After WCC1st ChangSha and the topic of 'Computing Ability', the
    author concluded his ten and six years of foundations and experiences,
    could detail a Computing and Its Energetic Optimization as below.
    <br/>
    <br/>The author considered the conception of 'Computing Ability' was
    a 'Computing Energy'. This was the future-world energies, although was
    not a new energy, but was a new topic. The author considered Its
    utilization's were out of a maximizing layer of human cognition. So took
    this topic and question, the author did good trending-conclusions as
    below.
    <br/>
    <br/>1 Foundational Computing Energy, the author considered the
    theory of out of humanoid-minding, which included DNA mask link and PDN
    Metabase Initons. ( 作者当时已经提出PDN AOPM VPCS catalyst 观点, 但2019年还没有发明
    PDN
    Extension, PDE metabolism 算法)
    <br/>
    <br/>2 Quantum-Computing Energy, the author considered the theory of
    Convolution, CNN, Vectors, Probability and Statistics.
    <br/>
    <br/>3 Ray-Computing Energy, the author considered the theory of FFT,
    DCT, Wavelet and Parallel Discrete Mathematics.
    <br/>
    <br/>4 Superconductor Computing Energy, the author considered the
    theory of Computing about non-resistance and fidelity.
    <br/>
    <br/>Seem their had more answers and domains, and one of considering,
    was humanoid-robot.
    <br/>
    <br/>Aboves pointed out emphatically, a Computing Energy determinate
    the Trending Computing. And belows could make more details to optimize
    the procedures of Computing Energy.
    <br/>
    <br/>1 Energetic Theory of Computing logic, the author considered a
    procedure were changed real world requirements into software functions.
    Because the subject was computer, means not human, so that will cause a
    problem, means computer will raise over the humanoid in the future.
    Once the computer's logic which does not was absorbed by human
    technologies and ethics, even Its ideology is higher than human's mind.
    It is causing the Energetic Evolution.
    <br/>
    <br/>2 Mode Acquisition of Computing data set, the author considered
    a unified observation of Data pre-process. Recently became a more
    important topic in the real-world industrial environment.
    <br/>
    <br/>3 Filter Decision of Computing procedure, the author considered
    a reusable algorithm-technology, and this conception of authors from
    his sonar-lint experience at Folsom Intel.
    <br/>
    <br/>4 Optimization Assessment of Computing-result, the author
    considered a software engineering topic, such as a water fall mode, the
    aspect of software maintenance and customer assessment, were also
    important too.
    <br/>
    <br/>5 VISO Theory of Computing Evolutionary, of cause a good
    developing observation of the software statement, the author also
    considered either the Energetic Optimization could be promoted on a
    good way, or the energetic system could be fixed immediately, or both
    well.
    <br/>
    <br/>Finally, the author did a definition of energetic formula: N =
    S(AON)/ s(AON).
    <br/>
    <br/>Energetic unit= Under the unfinished perform-statement, the
    amount of AON looped by function per each second/ The amount of
    non-duplicated AON units by function needs.
    <br/>
    <br/>(AON) = And, Or, Negative Gate. N= Energetic unit. S(AON)=
    Under the unfinished perform statement, the amount of AON looped by
    function per each second. s(AON)= The amount of non-duplicated AON
    units by function needs.
    <br/>
    <br/>2019-09-14 Peking times 04:34
    <br/>
    <br/>Author YaoguangLuo 稍后纠正语法
    <br/>
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         alt="浏阳德塔软件开发有限公司,罗瑶光"/>

    <br/>函数集合
    <br/>
    <br/>1 德塔的数据分析包, 最早是作者在大学的处理 Rohini教授的 C语言数据结构《Data
    Structure》 和 Rein.Hart教授 计算机视觉卷积的《Computer Vision》课后作业.
    <br/>
    <br/>《Data Structure》refer page 226, 230, 235, 238, 253,
    作者没有把当年的计算器四则运算器和rotation tree等作业算法归纳在该作品中.
    <br/>
    <br/>《Computer Vision》refer page 202, 204, 205, 206, 209, 211, 212,
    213, 214, 217, 218, 220, 221, 259, 260,
    <br/>
    <br/>2 德塔的卷积在2013年后不断的完善, 发现其在仿生听觉和视觉计算中都能进行系统的应用,
    于是开始优化. refer page
    191.
    <br/>
    <br/>作者一开始设计卷积是路德大学图片上的应用, 2013年, 当ETL设计成了节点处理图片像素后,
    作者开始设计声音 java sound API的处理, 2014年. 这个引擎逐渐在计算机仿生系统中进行集成应用.
    论证了其在具体应用工程中的实践价值. 作者当时设计了主要用来测测作者自己的心跳.
    <br/>
    <br/>3 优化方式为将计算函数进行插件接口模式封装成jar, 方便上层调用. refer page 190.
    <br/>
    <br/>4 封装的过程中, 不断的进行细化优化, 衍生出多个辅助计算函数集, 如催化排序, 仿生滤波.
    refer page 247,
    655.
    <br/>
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         alt="浏阳德塔软件开发有限公司,罗瑶光"/>

    <br/>UML
    <br/>

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